def __add__(self, other):
from pandas.core.index import Index
from pandas.core.indexes.timedeltas import TimedeltaIndex
from pandas.tseries.offsets import DateOffset
other = lib.item_from_zerodim(other)
if isinstance(other, ABCSeries):
return NotImplemented
elif is_timedelta64_dtype(other):
return self._add_delta(other)
elif isinstance(other, (DateOffset, timedelta)):
return self._add_delta(other)
elif is_offsetlike(other):
# Array/Index of DateOffset objects
return self._add_offset_array(other)
elif isinstance(self, TimedeltaIndex) and isinstance(other, Index):
if hasattr(other, '_add_delta'):
return other._add_delta(self)
raise TypeError("cannot add TimedeltaIndex and {typ}"
.format(typ=type(other)))
elif is_integer(other):
return self.shift(other)
elif isinstance(other, (datetime, np.datetime64)):
return self._add_datelike(other)
elif isinstance(other, Index):
return self._add_datelike(other)
elif is_integer_dtype(other) and self.freq is None:
# GH#19123
raise NullFrequencyError("Cannot shift with no freq")
else: # pragma: no cover
return NotImplemented
def __add__(self, other):
from pandas.core.index import Index
from pandas.core.indexes.timedeltas import TimedeltaIndex
from pandas.tseries.offsets import DateOffset
other = lib.item_from_zerodim(other)
if isinstance(other, ABCSeries):
return NotImplemented
elif is_timedelta64_dtype(other):
return self._add_delta(other)
elif isinstance(other, (DateOffset, timedelta)):
return self._add_delta(other)
elif is_offsetlike(other):
# Array/Index of DateOffset objects
return self._add_offset_array(other)
elif isinstance(self, TimedeltaIndex) and isinstance(other, Index):
if hasattr(other, '_add_delta'):
return other._add_delta(self)
raise TypeError("cannot add TimedeltaIndex and {typ}".format(
typ=type(other)))
elif is_integer(other):
return self.shift(other)
elif isinstance(other, (datetime, np.datetime64)):
return self._add_datelike(other)
elif isinstance(other, Index):
return self._add_datelike(other)
elif is_integer_dtype(other) and self.freq is None:
# GH#19123
raise NullFrequencyError("Cannot shift with no freq")
else: # pragma: no cover
return NotImplemented
def __sub__(self, other):
other = lib.item_from_zerodim(other)
if isinstance(other, (ABCSeries, ABCDataFrame)):
return NotImplemented
# scalar others
elif other is NaT:
result = self._sub_nat()
elif isinstance(other, (Tick, timedelta, np.timedelta64)):
result = self._add_delta(-other)
elif isinstance(other, DateOffset):
# specifically _not_ a Tick
result = self._add_offset(-other)
elif isinstance(other, (datetime, np.datetime64)):
result = self._sub_datetimelike_scalar(other)
elif lib.is_integer(other):
# This check must come after the check for np.timedelta64
# as is_integer returns True for these
maybe_integer_op_deprecated(self)
result = self._time_shift(-other)
elif isinstance(other, Period):
result = self._sub_period(other)
# array-like others
elif is_timedelta64_dtype(other):
# TimedeltaIndex, ndarray[timedelta64]
result = self._add_delta(-other)
elif is_offsetlike(other):
# Array/Index of DateOffset objects
result = self._addsub_offset_array(other, operator.sub)
elif is_datetime64_dtype(other) or is_datetime64tz_dtype(other):
# DatetimeIndex, ndarray[datetime64]
result = self._sub_datetime_arraylike(other)
elif is_period_dtype(other):
# PeriodIndex
result = self._sub_period_array(other)
elif is_integer_dtype(other):
maybe_integer_op_deprecated(self)
result = self._addsub_int_array(other, operator.sub)
elif isinstance(other, ABCIndexClass):
raise TypeError("cannot subtract {cls} and {typ}"
.format(cls=type(self).__name__,
typ=type(other).__name__))
elif is_float_dtype(other):
# Explicitly catch invalid dtypes
raise TypeError("cannot subtract {dtype}-dtype from {cls}"
.format(dtype=other.dtype,
cls=type(self).__name__))
elif is_extension_array_dtype(other):
# Categorical op will raise; defer explicitly
return NotImplemented
else: # pragma: no cover
return NotImplemented
if is_timedelta64_dtype(result) and isinstance(result, np.ndarray):
from pandas.core.arrays import TimedeltaArrayMixin
# TODO: infer freq?
return TimedeltaArrayMixin(result)
return result
def __sub__(self, other):
from pandas.core.index import Index
from pandas.core.indexes.datetimes import DatetimeIndex
from pandas.core.indexes.timedeltas import TimedeltaIndex
from pandas.tseries.offsets import DateOffset
other = lib.item_from_zerodim(other)
if is_timedelta64_dtype(other):
return self._add_delta(-other)
elif isinstance(self, TimedeltaIndex) and isinstance(other, Index):
if not isinstance(other, TimedeltaIndex):
raise TypeError(
"cannot subtract TimedeltaIndex and {typ}".format(
typ=type(other).__name__))
return self._add_delta(-other)
elif isinstance(other, DatetimeIndex):
return self._sub_datelike(other)
elif isinstance(other, (DateOffset, timedelta)):
return self._add_delta(-other)
elif is_integer(other):
return self.shift(-other)
elif isinstance(other, (datetime, np.datetime64)):
return self._sub_datelike(other)
elif isinstance(other, Period):
return self._sub_period(other)
elif is_offsetlike(other):
# Array/Index of DateOffset objects
return self._sub_offset_array(other)
elif isinstance(other, Index):
raise TypeError("cannot subtract {typ1} and {typ2}".format(
typ1=type(self).__name__, typ2=type(other).__name__))
else: # pragma: no cover
return NotImplemented
def __sub__(self, other):
other = lib.item_from_zerodim(other)
if isinstance(other, (ABCSeries, ABCDataFrame)):
return NotImplemented
# scalar others
elif other is NaT:
result = self._sub_nat()
elif isinstance(other, (Tick, timedelta, np.timedelta64)):
result = self._add_delta(-other)
elif isinstance(other, DateOffset):
# specifically _not_ a Tick
result = self._add_offset(-other)
elif isinstance(other, (datetime, np.datetime64)):
result = self._sub_datetimelike_scalar(other)
elif lib.is_integer(other):
# This check must come after the check for np.timedelta64
# as is_integer returns True for these
if not is_period_dtype(self):
maybe_integer_op_deprecated(self)
result = self._time_shift(-other)
elif isinstance(other, Period):
result = self._sub_period(other)
# array-like others
elif is_timedelta64_dtype(other):
# TimedeltaIndex, ndarray[timedelta64]
result = self._add_delta(-other)
elif is_offsetlike(other):
# Array/Index of DateOffset objects
result = self._addsub_offset_array(other, operator.sub)
elif is_datetime64_dtype(other) or is_datetime64tz_dtype(other):
# DatetimeIndex, ndarray[datetime64]
result = self._sub_datetime_arraylike(other)
elif is_period_dtype(other):
# PeriodIndex
result = self._sub_period_array(other)
elif is_integer_dtype(other):
if not is_period_dtype(self):
maybe_integer_op_deprecated(self)
result = self._addsub_int_array(other, operator.sub)
elif isinstance(other, ABCIndexClass):
raise TypeError("cannot subtract {cls} and {typ}".format(
cls=type(self).__name__, typ=type(other).__name__))
elif is_float_dtype(other):
# Explicitly catch invalid dtypes
raise TypeError("cannot subtract {dtype}-dtype from {cls}".format(
dtype=other.dtype, cls=type(self).__name__))
elif is_extension_array_dtype(other):
# Categorical op will raise; defer explicitly
return NotImplemented
else: # pragma: no cover
return NotImplemented
if is_timedelta64_dtype(result) and isinstance(result, np.ndarray):
from pandas.core.arrays import TimedeltaArrayMixin
# TODO: infer freq?
return TimedeltaArrayMixin(result)
return result
def __add__(self, other):
other = lib.item_from_zerodim(other)
if isinstance(other, (ABCSeries, ABCDataFrame)):
return NotImplemented
# scalar others
elif other is NaT:
result = self._add_nat()
elif isinstance(other, (Tick, timedelta, np.timedelta64)):
result = self._add_delta(other)
elif isinstance(other, DateOffset):
# specifically _not_ a Tick
result = self._add_offset(other)
elif isinstance(other, (datetime, np.datetime64)):
result = self._add_datetimelike_scalar(other)
elif lib.is_integer(other):
# This check must come after the check for np.timedelta64
# as is_integer returns True for these
if not is_period_dtype(self):
maybe_integer_op_deprecated(self)
result = self._time_shift(other)
# array-like others
elif is_timedelta64_dtype(other):
# TimedeltaIndex, ndarray[timedelta64]
result = self._add_delta(other)
elif is_offsetlike(other):
# Array/Index of DateOffset objects
result = self._addsub_offset_array(other, operator.add)
elif is_datetime64_dtype(other) or is_datetime64tz_dtype(other):
# DatetimeIndex, ndarray[datetime64]
return self._add_datetime_arraylike(other)
elif is_integer_dtype(other):
if not is_period_dtype(self):
maybe_integer_op_deprecated(self)
result = self._addsub_int_array(other, operator.add)
elif is_float_dtype(other):
# Explicitly catch invalid dtypes
raise TypeError("cannot add {dtype}-dtype to {cls}"
.format(dtype=other.dtype,
cls=type(self).__name__))
elif is_period_dtype(other):
# if self is a TimedeltaArray and other is a PeriodArray with
# a timedelta-like (i.e. Tick) freq, this operation is valid.
# Defer to the PeriodArray implementation.
# In remaining cases, this will end up raising TypeError.
return NotImplemented
elif is_extension_array_dtype(other):
# Categorical op will raise; defer explicitly
return NotImplemented
else: # pragma: no cover
return NotImplemented
if is_timedelta64_dtype(result) and isinstance(result, np.ndarray):
from pandas.core.arrays import TimedeltaArrayMixin
# TODO: infer freq?
return TimedeltaArrayMixin(result)
return result
def __sub__(self, other):
from pandas import Index
other = lib.item_from_zerodim(other)
if isinstance(other, (ABCSeries, ABCDataFrame)):
return NotImplemented
# scalar others
elif other is NaT:
result = self._sub_nat()
elif isinstance(other, (Tick, timedelta, np.timedelta64)):
result = self._add_delta(-other)
elif isinstance(other, DateOffset):
# specifically _not_ a Tick
result = self._add_offset(-other)
elif isinstance(other, (datetime, np.datetime64)):
result = self._sub_datelike(other)
elif is_integer(other):
# This check must come after the check for np.timedelta64
# as is_integer returns True for these
result = self.shift(-other)
elif isinstance(other, Period):
result = self._sub_period(other)
# array-like others
elif is_timedelta64_dtype(other):
# TimedeltaIndex, ndarray[timedelta64]
result = self._add_delta(-other)
elif is_offsetlike(other):
# Array/Index of DateOffset objects
result = self._addsub_offset_array(other, operator.sub)
elif is_datetime64_dtype(other) or is_datetime64tz_dtype(other):
# DatetimeIndex, ndarray[datetime64]
result = self._sub_datelike(other)
elif isinstance(other, Index):
raise TypeError("cannot subtract {cls} and {typ}"
.format(cls=type(self).__name__,
typ=type(other).__name__))
elif is_integer_dtype(other) and self.freq is None:
# GH#19123
raise NullFrequencyError("Cannot shift with no freq")
elif is_float_dtype(other):
# Explicitly catch invalid dtypes
raise TypeError("cannot subtract {dtype}-dtype from {cls}"
.format(dtype=other.dtype,
cls=type(self).__name__))
else: # pragma: no cover
return NotImplemented
if result is NotImplemented:
return NotImplemented
elif not isinstance(result, Index):
# Index.__new__ will choose appropriate subclass for dtype
result = Index(result)
res_name = ops.get_op_result_name(self, other)
result.name = res_name
return result
def __add__(self, other):
other = lib.item_from_zerodim(other)
if isinstance(other, (ABCSeries, ABCDataFrame)):
return NotImplemented
# scalar others
elif other is NaT:
result = self._add_nat()
elif isinstance(other, (Tick, timedelta, np.timedelta64)):
result = self._add_delta(other)
elif isinstance(other, DateOffset):
# specifically _not_ a Tick
result = self._add_offset(other)
elif isinstance(other, (datetime, np.datetime64)):
result = self._add_datetimelike_scalar(other)
elif lib.is_integer(other):
# This check must come after the check for np.timedelta64
# as is_integer returns True for these
maybe_integer_op_deprecated(self)
result = self._time_shift(other)
# array-like others
elif is_timedelta64_dtype(other):
# TimedeltaIndex, ndarray[timedelta64]
result = self._add_delta(other)
elif is_offsetlike(other):
# Array/Index of DateOffset objects
result = self._addsub_offset_array(other, operator.add)
elif is_datetime64_dtype(other) or is_datetime64tz_dtype(other):
# DatetimeIndex, ndarray[datetime64]
return self._add_datetime_arraylike(other)
elif is_integer_dtype(other):
maybe_integer_op_deprecated(self)
result = self._addsub_int_array(other, operator.add)
elif is_float_dtype(other):
# Explicitly catch invalid dtypes
raise TypeError("cannot add {dtype}-dtype to {cls}"
.format(dtype=other.dtype,
cls=type(self).__name__))
elif is_period_dtype(other):
# if self is a TimedeltaArray and other is a PeriodArray with
# a timedelta-like (i.e. Tick) freq, this operation is valid.
# Defer to the PeriodArray implementation.
# In remaining cases, this will end up raising TypeError.
return NotImplemented
elif is_extension_array_dtype(other):
# Categorical op will raise; defer explicitly
return NotImplemented
else: # pragma: no cover
return NotImplemented
if is_timedelta64_dtype(result) and isinstance(result, np.ndarray):
from pandas.core.arrays import TimedeltaArrayMixin
# TODO: infer freq?
return TimedeltaArrayMixin(result)
return result
def __add__(self, other):
other = lib.item_from_zerodim(other)
if isinstance(other, (ABCSeries, ABCDataFrame)):
return NotImplemented
# scalar others
elif other is NaT:
result = self._add_nat()
elif isinstance(other, (Tick, timedelta, np.timedelta64)):
result = self._add_delta(other)
elif isinstance(other, DateOffset):
# specifically _not_ a Tick
result = self._add_offset(other)
elif isinstance(other, (datetime, np.datetime64)):
result = self._add_datelike(other)
elif is_integer(other):
# This check must come after the check for np.timedelta64
# as is_integer returns True for these
result = self.shift(other)
# array-like others
elif is_timedelta64_dtype(other):
# TimedeltaIndex, ndarray[timedelta64]
result = self._add_delta(other)
elif is_offsetlike(other):
# Array/Index of DateOffset objects
result = self._addsub_offset_array(other, operator.add)
elif is_datetime64_dtype(other) or is_datetime64tz_dtype(other):
# DatetimeIndex, ndarray[datetime64]
return self._add_datelike(other)
elif is_integer_dtype(other):
result = self._addsub_int_array(other, operator.add)
elif is_float_dtype(other) or is_period_dtype(other):
# Explicitly catch invalid dtypes
raise TypeError("cannot add {dtype}-dtype to {cls}"
.format(dtype=other.dtype,
cls=type(self).__name__))
elif is_categorical_dtype(other):
# Categorical op will raise; defer explicitly
return NotImplemented
else: # pragma: no cover
return NotImplemented
if result is NotImplemented:
return NotImplemented
elif not isinstance(result, Index):
# Index.__new__ will choose appropriate subclass for dtype
result = Index(result)
res_name = ops.get_op_result_name(self, other)
result.name = res_name
return result
def __sub__(self, other):
from pandas import Index, DatetimeIndex, TimedeltaIndex, DateOffset
other = lib.item_from_zerodim(other)
if isinstance(other, ABCSeries):
return NotImplemented
# scalar others
elif isinstance(other, (DateOffset, timedelta, np.timedelta64)):
result = self._add_delta(-other)
elif isinstance(other, (datetime, np.datetime64)):
result = self._sub_datelike(other)
elif is_integer(other):
# This check must come after the check for np.timedelta64
# as is_integer returns True for these
result = self.shift(-other)
elif isinstance(other, Period):
result = self._sub_period(other)
# array-like others
elif is_timedelta64_dtype(other):
# TimedeltaIndex, ndarray[timedelta64]
result = self._add_delta(-other)
elif is_offsetlike(other):
# Array/Index of DateOffset objects
result = self._addsub_offset_array(other, operator.sub)
elif isinstance(self, TimedeltaIndex) and isinstance(other, Index):
# We checked above for timedelta64_dtype(other) so this
# must be invalid.
raise TypeError(
"cannot subtract TimedeltaIndex and {typ}".format(
typ=type(other).__name__))
elif isinstance(other, DatetimeIndex):
result = self._sub_datelike(other)
elif is_datetime64_dtype(other):
# ndarray[datetime64]; note we caught DatetimeIndex earlier
return self - DatetimeIndex(other)
elif isinstance(other, Index):
raise TypeError("cannot subtract {typ1} and {typ2}".format(
typ1=type(self).__name__, typ2=type(other).__name__))
elif is_integer_dtype(other) and self.freq is None:
# GH#19123
raise NullFrequencyError("Cannot shift with no freq")
else: # pragma: no cover
return NotImplemented
if result is not NotImplemented:
res_name = ops.get_op_result_name(self, other)
result.name = res_name
return result
def test_is_offsetlike():
assert com.is_offsetlike(np.array([pd.DateOffset(month=3), pd.offsets.Nano()]))
assert com.is_offsetlike(pd.offsets.MonthEnd())
assert com.is_offsetlike(pd.Index([pd.DateOffset(second=1)]))
assert not com.is_offsetlike(pd.Timedelta(1))
assert not com.is_offsetlike(np.array([1 + 1j, 5]))
# mixed case
assert not com.is_offsetlike(np.array([pd.DateOffset(), pd.Timestamp(0)]))
def __add__(self, other):
from pandas import Index, DatetimeIndex, TimedeltaIndex, DateOffset
other = lib.item_from_zerodim(other)
if isinstance(other, ABCSeries):
return NotImplemented
# scalar others
elif isinstance(other, (DateOffset, timedelta, np.timedelta64)):
result = self._add_delta(other)
elif isinstance(other, (datetime, np.datetime64)):
result = self._add_datelike(other)
elif is_integer(other):
# This check must come after the check for np.timedelta64
# as is_integer returns True for these
result = self.shift(other)
# array-like others
elif is_timedelta64_dtype(other):
# TimedeltaIndex, ndarray[timedelta64]
result = self._add_delta(other)
elif is_offsetlike(other):
# Array/Index of DateOffset objects
result = self._addsub_offset_array(other, operator.add)
elif isinstance(self, TimedeltaIndex) and isinstance(other, Index):
if hasattr(other, '_add_delta'):
# i.e. DatetimeIndex, TimedeltaIndex, or PeriodIndex
result = other._add_delta(self)
else:
raise TypeError(
"cannot add TimedeltaIndex and {typ}".format(
typ=type(other)))
elif isinstance(other, Index):
result = self._add_datelike(other)
elif is_datetime64_dtype(other):
# ndarray[datetime64]; note DatetimeIndex is caught above
return self + DatetimeIndex(other)
elif is_integer_dtype(other) and self.freq is None:
# GH#19123
raise NullFrequencyError("Cannot shift with no freq")
else: # pragma: no cover
return NotImplemented
if result is not NotImplemented:
res_name = ops.get_op_result_name(self, other)
result.name = res_name
return result
def test_is_offsetlike():
assert com.is_offsetlike(np.array([pd.DateOffset(month=3),
pd.offsets.Nano()]))
assert com.is_offsetlike(pd.offsets.MonthEnd())
assert com.is_offsetlike(pd.Index([pd.DateOffset(second=1)]))
assert not com.is_offsetlike(pd.Timedelta(1))
assert not com.is_offsetlike(np.array([1 + 1j, 5]))
# mixed case
assert not com.is_offsetlike(np.array([pd.DateOffset(), pd.Timestamp(0)]))
def __sub__(self, other):
from pandas.core.index import Index
from pandas.core.indexes.datetimes import DatetimeIndex
from pandas.core.indexes.timedeltas import TimedeltaIndex
from pandas.tseries.offsets import DateOffset
other = lib.item_from_zerodim(other)
if isinstance(other, ABCSeries):
return NotImplemented
elif is_timedelta64_dtype(other):
result = self._add_delta(-other)
elif isinstance(other, (DateOffset, timedelta)):
result = self._add_delta(-other)
elif is_offsetlike(other):
# Array/Index of DateOffset objects
result = self._sub_offset_array(other)
elif isinstance(self, TimedeltaIndex) and isinstance(other, Index):
if not isinstance(other, TimedeltaIndex):
raise TypeError("cannot subtract TimedeltaIndex and {typ}"
.format(typ=type(other).__name__))
result = self._add_delta(-other)
elif isinstance(other, DatetimeIndex):
result = self._sub_datelike(other)
elif is_integer(other):
# This check must come after the check for timedelta64_dtype
# or else it will incorrectly catch np.timedelta64 objects
result = self.shift(-other)
elif isinstance(other, (datetime, np.datetime64)):
result = self._sub_datelike(other)
elif isinstance(other, Period):
result = self._sub_period(other)
elif isinstance(other, Index):
raise TypeError("cannot subtract {typ1} and {typ2}"
.format(typ1=type(self).__name__,
typ2=type(other).__name__))
elif is_integer_dtype(other) and self.freq is None:
# GH#19123
raise NullFrequencyError("Cannot shift with no freq")
else: # pragma: no cover
return NotImplemented
if result is not NotImplemented:
res_name = ops.get_op_result_name(self, other)
result.name = res_name
return result
def __sub__(self, other):
from pandas.core.index import Index
from pandas.core.indexes.datetimes import DatetimeIndex
from pandas.core.indexes.timedeltas import TimedeltaIndex
from pandas.tseries.offsets import DateOffset
other = lib.item_from_zerodim(other)
if isinstance(other, ABCSeries):
return NotImplemented
elif is_timedelta64_dtype(other):
result = self._add_delta(-other)
elif isinstance(other, (DateOffset, timedelta)):
result = self._add_delta(-other)
elif is_offsetlike(other):
# Array/Index of DateOffset objects
result = self._sub_offset_array(other)
elif isinstance(self, TimedeltaIndex) and isinstance(other, Index):
if not isinstance(other, TimedeltaIndex):
raise TypeError(
"cannot subtract TimedeltaIndex and {typ}".format(
typ=type(other).__name__))
result = self._add_delta(-other)
elif isinstance(other, DatetimeIndex):
result = self._sub_datelike(other)
elif is_integer(other):
# This check must come after the check for timedelta64_dtype
# or else it will incorrectly catch np.timedelta64 objects
result = self.shift(-other)
elif isinstance(other, (datetime, np.datetime64)):
result = self._sub_datelike(other)
elif isinstance(other, Period):
result = self._sub_period(other)
elif isinstance(other, Index):
raise TypeError("cannot subtract {typ1} and {typ2}".format(
typ1=type(self).__name__, typ2=type(other).__name__))
elif is_integer_dtype(other) and self.freq is None:
# GH#19123
raise NullFrequencyError("Cannot shift with no freq")
else: # pragma: no cover
return NotImplemented
if result is not NotImplemented:
res_name = ops.get_op_result_name(self, other)
result.name = res_name
return result
def __add__(self, other):
from pandas import DateOffset
other = lib.item_from_zerodim(other)
if isinstance(other, ABCSeries):
return NotImplemented
# scalar others
elif other is NaT:
result = self._add_nat()
elif isinstance(other, (DateOffset, timedelta, np.timedelta64)):
result = self._add_delta(other)
elif isinstance(other, (datetime, np.datetime64)):
result = self._add_datelike(other)
elif is_integer(other):
# This check must come after the check for np.timedelta64
# as is_integer returns True for these
result = self.shift(other)
# array-like others
elif is_timedelta64_dtype(other):
# TimedeltaIndex, ndarray[timedelta64]
result = self._add_delta(other)
elif is_offsetlike(other):
# Array/Index of DateOffset objects
result = self._addsub_offset_array(other, operator.add)
elif is_datetime64_dtype(other) or is_datetime64tz_dtype(other):
# DatetimeIndex, ndarray[datetime64]
return self._add_datelike(other)
elif is_integer_dtype(other) and self.freq is None:
# GH#19123
raise NullFrequencyError("Cannot shift with no freq")
else: # pragma: no cover
return NotImplemented
if result is NotImplemented:
return NotImplemented
elif not isinstance(result, Index):
# Index.__new__ will choose appropriate subclass for dtype
result = Index(result)
res_name = ops.get_op_result_name(self, other)
result.name = res_name
return result
def __sub__(self, other):
from pandas.core.index import Index
from pandas.core.indexes.datetimes import DatetimeIndex
from pandas.core.indexes.timedeltas import TimedeltaIndex
from pandas.tseries.offsets import DateOffset
other = lib.item_from_zerodim(other)
if isinstance(other, ABCSeries):
return NotImplemented
elif is_timedelta64_dtype(other):
return self._add_delta(-other)
elif isinstance(other, (DateOffset, timedelta)):
return self._add_delta(-other)
elif is_offsetlike(other):
# Array/Index of DateOffset objects
return self._sub_offset_array(other)
elif isinstance(self, TimedeltaIndex) and isinstance(other, Index):
if not isinstance(other, TimedeltaIndex):
raise TypeError("cannot subtract TimedeltaIndex and {typ}"
.format(typ=type(other).__name__))
return self._add_delta(-other)
elif isinstance(other, DatetimeIndex):
return self._sub_datelike(other)
elif is_integer(other):
return self.shift(-other)
elif isinstance(other, (datetime, np.datetime64)):
return self._sub_datelike(other)
elif isinstance(other, Period):
return self._sub_period(other)
elif isinstance(other, Index):
raise TypeError("cannot subtract {typ1} and {typ2}"
.format(typ1=type(self).__name__,
typ2=type(other).__name__))
else: # pragma: no cover
return NotImplemented
